1. Field of Invention
The present invention relates to area-type digital image capture and processing systems having diverse modes of digital image processing for reading one-dimensional (1D) and two-dimensional (2D) bar code symbols, as well as other forms of graphically-encoded intelligence, employing advances methods of automatic illumination and imaging to meet demanding end-user application requirements.
2. Brief Description of the State of the Art
The state of the automatic-identification industry can be understood in terms of (i) the different classes of bar code symbologies that have been developed and adopted by the industry, and (ii) the kinds of apparatus developed and used to read such bar code symbologies in various user environments.
In general, there are currently three major classes of bar code symbologies, namely: one dimensional (1D) bar code symbologies, such as UPC/EAN, Code 39, etc.; 1D stacked bar code symbologies, Code 49, PDF417, etc.; and two-dimensional (2D) data matrix symbologies.
One-dimensional (1D) optical bar code readers are well known in the art. Examples of such readers include readers of the Metrologic Voyager® Series Laser Scanner manufactured by Metrologic Instruments, Inc. Such readers include processing circuits that are able to read one dimensional (1D) linear bar code symbologies, such as the UPC/EAN code, Code 39, etc., that are widely used in supermarkets. Such 1D linear symbologies are characterized by data that is encoded along a single axis, in the widths of bars and spaces, so that such symbols can be read from a single scan along that axis, provided that the symbol is imaged with a sufficiently high resolution along that axis.
In order to allow the encoding of larger amounts of data in a single bar code symbol, a number of 1D stacked bar code symbologies have been developed, including Code 49, as described in U.S. Pat. No. 4,794,239 (Allais), and PDF417, as described in U.S. Pat. No. 5,340,786 (Pavlidis, et al.). Stacked symbols partition the encoded data into multiple rows, each including a respective 1D bar code pattern, all or most of all of which must be scanned and decoded, then linked together to form a complete message. Scanning still requires relatively high resolution in one dimension only, but multiple linear scans are needed to read the whole symbol.
The third class of bar code symbologies, known as 2D matrix symbologies offer orientation-free scanning and greater data densities and capacities than their 1D counterparts. In 2D matrix codes, data is encoded as dark or light data elements within a regular polygonal matrix, accompanied by graphical finder, orientation and reference structures. When scanning 2D matrix codes, the horizontal and vertical relationships of the data elements are recorded with about equal resolution.
In order to avoid having to use different types of optical readers to read these different types of bar code symbols, it is desirable to have an optical reader that is able to read symbols of any of these types, including their various subtypes, interchangeably and automatically. More particularly, it is desirable to have an optical reader that is able to read all three of the above-mentioned types of bar code symbols, without human intervention, i.e., automatically. This is turn, requires that the reader have the ability to automatically discriminate between and decode bar code symbols, based only on information read from the symbol itself. Readers that have this ability are referred to as “auto-discriminating” or having an “auto-discrimination” capability.
If an auto-discriminating reader is able to read only 1D bar code symbols (including their various subtypes), it may be said to have a 1D auto-discrimination capability. Similarly, if it is able to read only 2D bar code symbols, it may be said to have a 2D auto-discrimination capability. If it is able to read both 1D and 2D bar code symbols interchangeably, it may be said to have a 1D/2D auto-discrimination capability. Often, however, a reader is said to have a 1D/2D auto-discrimination capability even if it is unable to discriminate between and decode 1D stacked bar code symbols.
Optical readers that are capable of 1D auto-discrimination are well known in the art. An early example of such a reader is Metrologic's VoyagerCG® Laser Scanner, manufactured by Metrologic Instruments, Inc.
Optical readers, particularly hand held optical readers, that are capable of 1D/2D auto-discrimination and based on the use of an asynchronously moving 1D image sensor, are described in U.S. Pat. Nos. 5,288,985 and 5,354,977, which applications are hereby expressly incorporated herein by reference. Other examples of hand held readers of this type, based on the use of a stationary 2D image sensor, are described in U.S. Pat. Nos. 6,250,551; 5,932,862; 5,932,741; 5,942,741; 5,929,418; 5,914,476; 5,831,254; 5,825,006; 5,784,102, which are also hereby expressly incorporated herein by reference.
Optical readers, whether of the stationary or movable type, usually operate at a fixed scanning rate, which means that the readers are designed to complete some fixed number of scans during a given amount of time. This scanning rate generally has a value that is between 30 and 200 scans/sec for 1D readers. In such readers, the results the successive scans are decoded in the order of their occurrence.
Imaging-based bar code symbol readers have a number advantages over laser scanning based bar code symbol readers, namely: they are more capable of reading stacked 2D symbologies, such as the PDF 417 symbology; more capable of reading matrix 2D symbologies, such as the Data Matrix symbology; more capable of reading bar codes regardless of their orientation; have lower manufacturing costs; and have the potential for use in other applications, which may or may not be related to bar code scanning, such as OCR, security systems, etc
Prior art digital image capture and processing systems suffer from a number of additional shortcomings and drawbacks.
Most prior art hand held optical reading devices can be reprogrammed by reading bar codes from a bar code programming menu or with use of a local host processor as taught in U.S. Pat. No. 5,929,418. However, these devices are generally constrained to operate within the modes in which they have been programmed to operate, either in the field or on the bench, before deployment to end-user application environments. Consequently, the statically-configured nature of such prior art imaging-based bar code reading systems has limited their performance.
Prior art digital image capture and processing systems with integrated illumination subsystems also support a relatively short range of the optical depth of field. This limits the capabilities of such systems from reading big or highly dense bar code labels.
Prior art digital image capture and processing systems generally require separate apparatus for producing a visible aiming beam to help the user to aim the camera's field of view at the bar code label on a particular target object.
Prior art digital image capture and processing systems generally require capturing multiple frames of image data of a bar code symbol, and special apparatus for synchronizing the decoding process with the image capture process within such readers, as required in U.S. Pat. Nos. 5,932,862 and 5,942,741 assigned to Welch Allyn, Inc.
Prior art digital image capture and processing systems generally require large arrays of LEDs in order to flood the field of view within which a bar code symbol might reside during image capture operations, oftentimes wasting large amounts of electrical power which can be significant in portable or mobile imaging-based readers.
Prior art digital image capture and processing systems generally require processing the entire pixel data set of capture images to find and decode bar code symbols represented therein. On the other hand, some prior art imaging systems use the inherent programmable (pixel) windowing feature within conventional CMOS image sensors to capture only partial image frames to reduce pixel data set processing and enjoy improvements in image processing speed and thus imaging system performance.
Many prior art digital image capture and processing systems also require the use of decoding algorithms that seek to find the orientation of bar code elements in a captured image by finding and analyzing the code words of 2-D bar code symbologies represented therein.
Some prior art digital image capture and processing systems generally require the use of a manually-actuated trigger to actuate the image capture and processing cycle thereof.
Prior art digital image capture and processing systems generally require separate sources of illumination for producing visible aiming beams and for producing visible illumination beams used to flood the field of view of the bar code reader.
Prior art digital image capture and processing systems generally utilize during a single image capture and processing cycle, and a single decoding methodology for decoding bar code symbols represented in captured images.
Some prior art digital image capture and processing systems require exposure control circuitry integrated with the image detection array for measuring the light exposure levels on selected portions thereof.
Also, many imaging-based readers also require processing portions of captured images to detect the image intensities thereof and determine the reflected light levels at the image detection component of the system, and thereafter to control the LED-based illumination sources to achieve the desired image exposure levels at the image detector.
Prior art digital image capture and processing systems employing integrated illumination mechanisms control image brightness and contrast by controlling the time that the image sensing device is exposed to the light reflected from the imaged objects. While this method has been proven for the CCD-based bar code scanners, it is not suitable, however, for the CMOS-based image sensing devices, which require a more sophisticated shuttering mechanism, leading to increased complexity, less reliability and, ultimately, more expensive bar code scanning systems.
Prior art digital image capture and processing systems generally require the use of tables and bar code menus to manage which decoding algorithms are to be used within any particular mode of system operation to be programmed by reading bar code symbols from a bar code menu.
Also, due to the complexity of the hardware platforms of such prior art digital image capture and processing systems, end-users are not permitted to modify the features and functionalities of such system to their customized application requirements, other than changing limited functions within the system by reading system-programming type bar code symbols, as disclosed in U.S. Pat. Nos. 6,321,989; 5,965,863; 5,929,418; and 5,932,862, each being incorporated herein by reference.
Also, dedicated image-processing based bar code symbol reading devices usually have very limited resources, such as the amount of volatile and non-volatile memories. Therefore, they usually do not have a rich set of tools normally available to universal computer systems. Further, if a customer or a third-party needs to enhance or alter the behavior of a conventional image-processing based bar code symbol reading system or device, they need to contact the device manufacturer and negotiate the necessary changes in the “standard” software or the ways to integrate their own software into the device, which usually involves the re-design or re-compilation of the software by the original equipment manufacturer (OEM). This software modification process is both costly and time consuming.
Prior Art Field of View (FOV) Aiming, Targeting, Indicating and Marking Techniques
The need to target, indicate and/or mark the field of view (FOV) of 1D and 2D image sensors within hand-held imagers has also been long recognized in the industry.
In U.S. Pat. No. 4,877,949, Danielson et a disclosed on Aug. 8, 1986 an digital image capture and processing system having a 2D image sensor with a field of view (FOV) and also a pair of LEDs mounted about a 1D (i.e. linear) image sensor to project a pair of light beams through the FOV focusing optics and produce a pair of spots on a target surface supporting a 1D bar code, thereby indicating the location of the FOV on the target and enable the user to align the bar code therewithin.
In U.S. Pat. No. 5,019,699, Koenck et al disclosed on Aug. 31, 1988 an digital image capture and processing system having a 2D image sensor with a field of view (FOV) and also a set of four LEDs (each with lenses) about the periphery of a 2D (i.e. area) image sensor to project four light beams through the FOV focusing optics and produce four spots on a target surface to mark the corners of the FOV intersecting with the target, to help the user align 1D and 2D bar codes therewithin in an easy manner.
In FIGS. 48-50 of U.S. Pat. Nos. 5,841,121 and 6,681,994, Koenck disclosed on Nov. 21, 1990, an digital image capture and processing system having a 2D image sensor with a field of view (FOV) and also apparatus for marking the perimeter of the FOV, using four light sources and light shaping optics (e.g. cylindrical lens).
In U.S. Pat. No. 5,378,883, Batterman et al disclosed on Jul. 29, 1991, a hand-held digital image capture and processing system having a 2D image sensor with a field of view (FOV) and also a laser light source and fixed lens to produce a spotter beam that helps the operator aim the reader at a candidate bar code symbol. As disclosed, the spotter beam is also used measure the distance to the bar code symbol during automatic focus control operations supported within the bar code symbol reader.
In U.S. Pat. No. 5,659,167, Wang et al disclosed on Apr. 5, 1994, an digital image capture and processing system comprising a 2D image sensor with a field of view (FOV), a user display for displaying a visual representation of a dataform (e.g. bar code symbol), and visual guide marks on the user display for indicating whether or not the dataform being imaged is in focus when its image is within the guide marks, and out of focus when its image is within the guide marks.
In U.S. Pat. No. 6,347,163, Roustaei disclosed on May 19, 1995, a system for reading 2D images comprising a 2D image sensor, an array of LED illumination sources, and an image framing device which uses a VLD for producing a laser beam and a light diffractive optical element for transforming the laser beam into a plurality of beamlets having a beam edge and a beamlet spacing at the 2D image, which is at least as large as the width of the 2D image.
In U.S. Pat. No. 5,783,811, Feng et al disclosed on Feb. 26, 1996, a portable imaging assembly comprising a 2D image sensor with a field of view (FOV) and also a set of LEDs and a lens array which produces a cross-hair type illumination pattern in the FOV for aiming the imaging assembly at a target.
In U.S. Pat. No. 5,793,033, Feng et al disclosed on Mar. 29, 1996, a portable imaging assembly comprising a 2D image sensor with a field of view (FOV), and a viewing assembly having a pivoting member which, when positioned a predetermined distance from the operator's eye, provides a view through its opening which corresponds to the target area (FOV) of the imaging assembly for displaying a visual representation of a dataform (e.g. bar code symbol).
In U.S. Pat. No. 5,780,834, Havens et al disclosed on May 14, 1996, a portable imaging and illumination optics assembly having a 2D image sensor with a field of view (FOV), an array of LEDs for illumination, and an aiming or spotting light (LED) indicating the location of the FOV.
In U.S. Pat. No. 5,949,057, Feng et al disclosed on Jan. 31, 1997, a portable imaging device comprising a 2D image sensor with a field of view (FOV), and first and second sets of targeting LEDs and first and second targeting optics, which produces first and second illumination targeting patterns, which substantially coincide to form a single illumination targeting pattern when the imaging device is arranged at a “best focus” position.
In U.S. Pat. No. 6,060,722, Havens et al disclosed on Sep. 24, 1997, a portable imaging and illumination optics assembly comprising a 2D image sensor with a field of view (FOV), an array of LEDs for illumination, and an aiming pattern generator including at least a point-like aiming light source and a light diffractive element for producing an aiming pattern that remains approximately coincident with the FOV of the imaging device over the range of the reader-to-target distances over which the reader is used.
In U.S. Pat. No. 6,340,114, filed Jun. 12, 1998, Correa et al disclosed an imaging engine comprising a 2D image sensor with a field of view (FOV) and an aiming pattern generator using one or more laser diodes and one or more light diffractive elements to produce multiple aiming frames having different, partially overlapping, solid angle fields or dimensions corresponding to the different fields of view of the lens assembly employed in the imaging engine. The aiming pattern includes a centrally-located marker or cross-hair pattern. Each aiming frame consists of four corner markers, each comprising a plurality of illuminated spots, for example, two multiple spot lines intersecting at an angle of 90 degrees.
As a result of limitations in the field of view (FOV) marking, targeting and pointing subsystems employed within prior art digital image capture and processing systems, such prior art readers generally fail to enable users to precisely identify which portions of the FOV read high-density 1D bar codes with the ease and simplicity of laser scanning based bar code symbol readers, and also 2D symbologies, such as PDF 417 and Data Matrix.
Also, as a result of limitations in the mechanical, electrical, optical, and software design of prior art digital image capture and processing systems, such prior art readers generally: (i) fail to enable users to read high-density 1D bar codes with the ease and simplicity of laser scanning based bar code symbol readers and also 2D symbologies, such as PDF 417 and Data Matrix, and (iii) have not enabled end-users to modify the features and functionalities of such prior art systems without detailed knowledge about the hard-ware platform, communication interfaces and the user interfaces of such systems.
Also, control operations in prior art image-processing bar code symbol reading systems have not been sufficiently flexible or agile to adapt to the demanding lighting conditions presented in challenging retail and industrial work environments where 1D and 2D bar code symbols need to be reliably read.
Prior art digital imaging and laser scanning systems also suffering from a number of other problems as well.
Some prior art imaging systems have relied on IR-based object detection using the same image sensing array for detecting images of objects, and therefore, require that the decode microprocessor be powered up during the object detection state of operation, and consuming power which would be undesirable in portable digital imaging applications.
Thus, there is a great need in the art for an improved method of and apparatus for reading bar code symbols using image capture and processing techniques which avoid the shortcomings and drawbacks of prior art methods and apparatus.